As an important part of basic necessities of life, clothing manufacturing not only plays an important role in people's lives, but also plays an important role in economic development. It not only provides a large number of employment opportunities, promotes international trade and economic development, but also promotes technological innovation and the satisfaction of consumer demand. In order to comply with the new trend of digital economy development, the garment manufacturing industry is in the wave of digital transformation, and digital reform is in full swing.
1. The status quo of digitalization in garment manufacturing industry
(1) Informatization infrastructure has been completed and a large amount of data has been accumulated
Data islands: The information system data created by each manufacturer cannot be fully connected.
Development lever: A large amount of data is waiting to be mined and analyzed for value, which requires the introduction of artificial intelligence.
Human factors risk: Human labor will cause data security problems, fatigue and misoperation problems.
(2) Main goals of digitalization
Basic goal: to reduce labor costs by introducing automated digital employees to replace inefficient and repetitive manual work such as data processing and process operations.
Advanced goal: To improve work efficiency by introducing intelligent digital employees to replace cognitive and experiential mental work such as data review and process decision-making.
Ultimate goal: Through the introduction of digital employees and artificial intelligence technology, study, research and precipitate massive data, and mine data value to empower development.
2. The current main pain points in the clothing industry
(1) The complexity of production and supply chain management
The production and supply chain of the apparel industry is very complex, involving multiple links and participants, such as design, procurement, production, logistics, etc. The tediousness and complexity of production and supply chain management is a major pain point in the apparel industry.
(2) Inventory management and sales forecast
Due to factors such as seasonality and fashion, inventory management and sales forecasting in the apparel industry has become very difficult. There is often a backlog of inventory or poor sales, resulting in economic losses.
(3) Marketing and consumer experience
In the clothing industry, how to attract consumers, improve brand loyalty and purchase conversion rate is an important challenge. Marketing strategy and consumer experience design are critical to the success of an apparel business.
(4) Production environment and labor rights
The production environment and labor rights issues in the apparel industry have always attracted much attention. Due to price pressure and supply chain complexity, some apparel companies may ignore the production environment and labor rights issues, which has a negative impact on the industry image and corporate reputation.
(5) Sustainability and environmental issues
With increasing awareness of global warming and environmental protection, consumers are paying more and more attention to sustainability and environmental protection issues in the apparel industry. Apparel companies need to pay attention to product environmental protection, resource utilization and waste disposal to meet consumers' requirements for sustainability and environmental protection.
3. One-stop solution for digital employees
(1) Automation solution
Process automation : instead of manual work, realize process-oriented and repetitive software operation work instead of typical tasks such as tax declaration and invoicing.
Data automation: Instead of interfaces, realize cross-system and cross-application data connections. Typical example: online banking flow import.
(2) Intelligent solutions
Basic intelligence: Invoke basic AI capabilities to assist basic functions of intelligent applications, such as: OCR bill recognition.
Business intelligence: train business AI models to realize the intelligence of business scenarios, such as: smart contract review.
(3) Global data solutions
Data collection: data structured processing and batch collection based on artificial intelligence; automatic batch collection based on automation.
Data storage: seamlessly connect to mainstream databases; synchronize ultra-automated full-business scenario data through a lightweight data center.
Data application: supports BI data analysis and large data screen; supports AI data modeling to realize intelligent analysis and prediction of data.
4. Application Scenarios of RPA in Garment Manufacturing
(1) Online banking reconciliation
Automatically activate the USB shield to log in to the online banking system, automatically synchronize the online banking flow records to the financial system at regular intervals, automatically check the differences in transaction details and issue a balance adjustment form.
(2) Expense statement
Automatically log in to the financial system, query expense data by department, generate department expense reports according to the template requirements, and send the reports to the person in charge of the corresponding department.
(3) Invoice Verification
Extract the key information of the invoice, and check the authenticity and repeatability
(4) Reimbursement approval
Content review of specific bills: consistency between small bills and reimbursement amounts; exclusion of medical category C reimbursement items
5. Customer case
Industry background: Improve quality, reduce cost, increase efficiency, and empower manufacturing digital transformation
Center of Excellence: Coordinate and promote the top-level design of the digital employee platform, build a digital center of excellence, and promote the digitalization process of enterprises.
Shared services: Accumulate the shared service capabilities of digital employees, and promote the improvement of quality, cost and efficiency of daily operations of enterprises.
Main pain point: Many docking systems: ERP/MES/TMS... There are many entities in the company and the data granularity is fine.
Main application: IPA: controller + designer + robot AI: Chatbot+IDP+BI+DI
(1) Real Intelligence × Anzheng Group
Project background
Cross-platform operation, the data of each platform cannot be obtained through the interface, and data collection requires a lot of labor.
Project content
Multi-platform business data analysis Taobao, JD.com and other mainstream platform business data collection and summary in real time, real-time monitoring of key indicators of store operating conditions on each platform, monitoring of key indicators of market conditions, real-time monitoring.
(2) Real Intelligence×Mengmoge
Project background
Intelligent automation of customer service business: In the process of customer service, a large number of business data have been accumulated, and data value mining is required.
Project Content
Customer Evaluation Classification: Intelligently discover commodity problems and service problem feedback hidden in praise, and guide product and service improvement.
Intelligent handling of complaints: intelligently identify appeals and automatically send them to corresponding personnel for processing.
Project effectiveness
Tens of thousands of evaluations, automatic classification and extraction of key information, intelligent complaint reception, greatly improved the efficiency of complaint handling, and promoted the improvement of manual efficiency by more than 50%.
(3) Real Smart × Winner Fashion
Project background
Store operation data management: There are various types of cash register systems in commercial complexes, and interfaces cannot be provided, and the timeliness of store operation data acquisition is poor.
Project content
Automatic collection of store data: unified and automatic collection of store operating data across the country to realize integrated management of offline and online operating data.
Financial intelligent automation: automatic invoicing, automatic tax declaration and other
project results
. Commercial complex system; automatic docking replaces manual work to ensure the correctness of data processing; realizes integrated management of online and offline business data.
(4) Real Intelligence × Ordos
Project Background
Collaborative supply chain management, scattered warehouse data, and manual acquisition methods are prone to errors.
Project content
Warehousing data monitoring: Regent System, Vipshop and other three-party warehouse data are automatically and real-time queried and reported in a unified manner.
Supplier information maintenance: automatically review and update supplier information.
Project effectiveness
Daily regular query and summary to ensure data timeliness; automatic docking replaces manual work to ensure 1010% correctness of data processing; automatic review of key supplier information to avoid human risk.
(5) Real Intelligence × Jingwei Textile Machinery
Project background
Financial digital employees: Online banking data processing and other processes need to be executed periodically, and the data security and accuracy requirements are high.
Project content
Online banking process automation: online banking flow is automatically downloaded and electronic receipts are automatically archived, non-directly connected account balances are automatically imported, and online banking is automatically reconciled.
Report processing automation: Business reports are automatically generated.
Project effectiveness
Save labor costs by 70%; increase repetitive work efficiency by 300%; ensure data processing accuracy by 100%;
(6) Real Intelligence × CVTE
Project background
CVTE's business and financial integration: Starting from the sales management department and the financial department, promote the digitalization process of the group as a whole.
Project content
Tax process automation: automatic monthly tax declaration in multiple provinces, and automatic issuance of invoices based on contract orders.
Intelligent contract review: identification and review of key information of overseas customer contracts.
Project effectiveness
The nuclear efficiency has been increased by 10 times; IDP smart documents are used to realize intelligent contract review.